no code implementations • ACL 2022 • Bingsheng Yao, Dakuo Wang, Tongshuang Wu, Zheng Zhang, Toby Li, Mo Yu, Ying Xu
Existing question answering (QA) techniques are created mainly to answer questions asked by humans.
no code implementations • ACL 2022 • Ying Xu, Dakuo Wang, Mo Yu, Daniel Ritchie, Bingsheng Yao, Tongshuang Wu, Zheng Zhang, Toby Li, Nora Bradford, Branda Sun, Tran Hoang, Yisi Sang, Yufang Hou, Xiaojuan Ma, Diyi Yang, Nanyun Peng, Zhou Yu, Mark Warschauer
Through benchmarking with QG models, we show that the QG model trained on FairytaleQA is capable of asking high-quality and more diverse questions.
1 code implementation • 26 Feb 2023 • Ying Xu, Kiran Raja, Luisa Verdoliva, Marius Pedersen
We obtain 98. 48% BOSC accuracy on the FF++ dataset and 90. 87% BOSC accuracy on the CelebDF dataset suggesting a promising direction for generalization of DeepFake detection.
no code implementations • 14 Dec 2022 • Ying Xu, Samalika Perera, Yeshwanth Bethi, Saeed Afshar, André van Schaik
This paper presents a reconfigurable digital implementation of an event-based binaural cochlear system on a Field Programmable Gate Array (FPGA).
no code implementations • 14 Nov 2022 • Ying Xu, Romane Gauriau, Anna Decker, Jacob Oppenheim
Understanding patterns of diagnoses, medications, procedures, and laboratory tests from electronic health records (EHRs) and health insurer claims is important for understanding disease risk and for efficient clinical development, which often require rules-based curation in collaboration with clinicians.
no code implementations • 27 Sep 2022 • Ying Xu, Sule Yildirim Yayilgan
We also check the performance of these features when there are mismatches between training sets and test sets.
1 code implementation • IEEE Access 2022 • Yeshwanth Bethi, Ying Xu, Gregory Cohen, André van Schaik, and Saeed Afshar
Through the use of simple local adaptive selection thresholds at each node, the network rapidly learns to appropriately allocate its neuronal resources at each layer for any given problem without using an error measure.
1 code implementation • 11 Aug 2022 • Ying Xu, Philipp Terhörst, Kiran Raja, Marius Pedersen
In this work, we investigate the bias issue caused by public Deepfake datasets by (a) providing large-scale demographic and non-demographic attribute annotations of 47 different attributes for five popular Deepfake datasets and (b) comprehensively analysing AI-bias of three state-of-the-art Deepfake detection backbone models on these datasets.
no code implementations • 3 Jul 2022 • Weiming Zhuang, Chongjie Ye, Ying Xu, Pengzhi Mao, Shuai Zhang
In this demo, we present Chat-to-Design, a new multimodal interaction system for personalized fashion design.
no code implementations • 22 Jun 2022 • Sebastian Gehrmann, Abhik Bhattacharjee, Abinaya Mahendiran, Alex Wang, Alexandros Papangelis, Aman Madaan, Angelina McMillan-Major, Anna Shvets, Ashish Upadhyay, Bingsheng Yao, Bryan Wilie, Chandra Bhagavatula, Chaobin You, Craig Thomson, Cristina Garbacea, Dakuo Wang, Daniel Deutsch, Deyi Xiong, Di Jin, Dimitra Gkatzia, Dragomir Radev, Elizabeth Clark, Esin Durmus, Faisal Ladhak, Filip Ginter, Genta Indra Winata, Hendrik Strobelt, Hiroaki Hayashi, Jekaterina Novikova, Jenna Kanerva, Jenny Chim, Jiawei Zhou, Jordan Clive, Joshua Maynez, João Sedoc, Juraj Juraska, Kaustubh Dhole, Khyathi Raghavi Chandu, Laura Perez-Beltrachini, Leonardo F. R. Ribeiro, Lewis Tunstall, Li Zhang, Mahima Pushkarna, Mathias Creutz, Michael White, Mihir Sanjay Kale, Moussa Kamal Eddine, Nico Daheim, Nishant Subramani, Ondrej Dusek, Paul Pu Liang, Pawan Sasanka Ammanamanchi, Qi Zhu, Ratish Puduppully, Reno Kriz, Rifat Shahriyar, Ronald Cardenas, Saad Mahamood, Salomey Osei, Samuel Cahyawijaya, Sanja Štajner, Sebastien Montella, Shailza, Shailza Jolly, Simon Mille, Tahmid Hasan, Tianhao Shen, Tosin Adewumi, Vikas Raunak, Vipul Raheja, Vitaly Nikolaev, Vivian Tsai, Yacine Jernite, Ying Xu, Yisi Sang, Yixin Liu, Yufang Hou
This problem is especially pertinent in natural language generation which requires ever-improving suites of datasets, metrics, and human evaluation to make definitive claims.
1 code implementation • 26 Mar 2022 • Ying Xu, Dakuo Wang, Mo Yu, Daniel Ritchie, Bingsheng Yao, Tongshuang Wu, Zheng Zhang, Toby Jia-Jun Li, Nora Bradford, Branda Sun, Tran Bao Hoang, Yisi Sang, Yufang Hou, Xiaojuan Ma, Diyi Yang, Nanyun Peng, Zhou Yu, Mark Warschauer
Through benchmarking with QG models, we show that the QG model trained on FairytaleQA is capable of asking high-quality and more diverse questions.
Ranked #1 on
Question Generation
on FairytaleQA
1 code implementation • 13 Feb 2022 • Zheng Zhang, Ying Xu, Yanhao Wang, Bingsheng Yao, Daniel Ritchie, Tongshuang Wu, Mo Yu, Dakuo Wang, Toby Jia-Jun Li
Despite its benefits for children's skill development and parent-child bonding, many parents do not often engage in interactive storytelling by having story-related dialogues with their child due to limited availability or challenges in coming up with appropriate questions.
no code implementations • 27 Sep 2021 • Yeshwanth Bethi, Ying Xu, Gregory Cohen, Andre van Schaik, Saeed Afshar
Through the use of simple local adaptive selection thresholds at each node, the network rapidly learns to appropriately allocate its neuronal resources at each layer for any given problem without using a real-valued error measure.
2 code implementations • 8 Sep 2021 • Bingsheng Yao, Dakuo Wang, Tongshuang Wu, Zheng Zhang, Toby Jia-Jun Li, Mo Yu, Ying Xu
Existing question answering (QA) techniques are created mainly to answer questions asked by humans.
1 code implementation • 29 Jul 2021 • Chongyang Bai, Xiaoxue Zang, Ying Xu, Srinivas Sunkara, Abhinav Rastogi, Jindong Chen, Blaise Aguera y Arcas
Our key intuition is that the heterogeneous features in a UI are self-aligned, i. e., the image and text features of UI components, are predictive of each other.
no code implementations • 9 Jul 2021 • Xiaoxue Zang, Ying Xu, Jindong Chen
Annotating user interfaces (UIs) that involves localization and classification of meaningful UI elements on a screen is a critical step for many mobile applications such as screen readers and voice control of devices.
no code implementations • NAACL 2021 • Ying Xu, Xu Zhong, Antonio Jimeno Yepes, Jey Han Lau
We introduce a grey-box adversarial attack and defence framework for sentiment classification.
no code implementations • 20 Jan 2021 • Ying Xu, Zhihua Qu
The unique problems and phenomena in the distributed voltage control of large-scale power distribution systems with extremely-high DER-penetration are targeted in this paper.
no code implementations • 17 Jan 2021 • Stefan Maetschke, David Martinez Iraola, Pieter Barnard, Elaheh ShafieiBavani, Peter Zhong, Ying Xu, Antonio Jimeno Yepes
A question remains of how much understanding is leveraged by these methods and how appropriate are the current benchmarks to measure understanding capabilities.
no code implementations • 22 Dec 2020 • Zecheng He, Srinivas Sunkara, Xiaoxue Zang, Ying Xu, Lijuan Liu, Nevan Wichers, Gabriel Schubiner, Ruby Lee, Jindong Chen, Blaise Agüera y Arcas
Our methodology is designed to leverage visual, linguistic and domain-specific features in user interaction traces to pre-train generic feature representations of UIs and their components.
no code implementations • 27 Aug 2020 • Dongming Han, Wei Chen, Rusheng Pan, Yijing Liu, Jiehui Zhou, Ying Xu, Tianye Zhang, Changjie Fan, Jianrong Tao, Xiaolong, Zhang
This paper presents GraphFederator, a novel approach to construct joint representations of multi-party graphs and supports privacy-preserving visual analysis of graphs.
Human-Computer Interaction Cryptography and Security Graphics
no code implementations • 24 May 2020 • Donghui Yan, Ying Xu, Pei Wang
We propose a structured approach for the estimation of the number of unreported cases, where we distinguish cases that arrive late in the reported numbers and those who had mild or no symptoms and thus were not captured by any medical system at all.
no code implementations • 22 Jan 2020 • Ying Xu, Xu Zhong, Antonio Jose Jimeno Yepes, Jey Han Lau
An adversarial example is an input transformed by small perturbations that machine learning models consistently misclassify.
no code implementations • 28 Aug 2019 • Donghui Yan, Songxiang Gu, Ying Xu, Zhiwei Qin
Similarity plays a fundamental role in many areas, including data mining, machine learning, statistics and various applied domains.
no code implementations • 30 Jul 2019 • Donghui Yan, Ying Xu
This framework only requires a small amount of local signatures to be shared among distributed sites, eliminating the need of having to transmitting big data.
no code implementations • 18 Jul 2019 • Saeed Afshar, Ying Xu, Jonathan Tapson, André van Schaik, Gregory Cohen
A novel heuristic method for network size selection is proposed which makes use of noise events and their feature representations.
no code implementations • WS 2017 • Ying Xu, Jey Han Lau, Timothy Baldwin, Trevor Cohn
With this decoupled architecture, we decrease the number of parameters in the decoder substantially, and shorten its training time.
no code implementations • 3 Sep 2015 • Ying Xu, Chetan Singh Thakur, Tara Julia Hamilton, Jonathan Tapson, Runchun Wang, Andre van Schaik
The architecture consists of an analogue chip and a control module.